• Open Access

Cell Lineage Statistics with Incomplete Population Trees

Arthur Genthon, Takashi Nozoe, Luca Peliti, and David Lacoste
PRX Life 1, 013014 – Published 7 September 2023

Abstract

Cell lineage statistics is a powerful tool for inferring cellular parameters, such as division rate, death rate, or population growth rate. Yet, in practice such an analysis suffers from a basic problem: how should we treat incomplete lineages that do not survive until the end of the experiment? Here, we develop a model-independent theoretical framework to address this issue. We show how to quantify fitness landscape, survivor bias, and selection for arbitrary cell traits from cell lineage statistics in the presence of death, and we test this method using an experimental data set in which a cell population is exposed to a drug that kills a large fraction of the population. This analysis reveals that failing to properly account for dead lineages can lead to misleading fitness estimations. For simple trait dynamics, we prove and illustrate numerically that the fitness landscape and the survivor bias can in addition be used for the nonparametric estimation of the division and death rates, using only lineage histories. Our framework provides universal bounds on the population growth rate, and a fluctuation-response relation that quantifies the change in population growth rate due to the variability in death rate. Further, in the context of cell size control, we obtain generalizations of Powell's relation that link the distributions of generation times with the population growth rate, and we show that the survivor bias can sometimes conceal the adder property, namely the constant increment of volume between birth and division.

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  • Received 25 April 2023
  • Accepted 7 August 2023

DOI:https://doi.org/10.1103/PRXLife.1.013014

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsStatistical Physics & Thermodynamics

Authors & Affiliations

Arthur Genthon1,2,*, Takashi Nozoe3,4,5, Luca Peliti6, and David Lacoste2

  • 1Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
  • 2Gulliver UMR CNRS 7083, ESPCI Paris, Université PSL, 75005 Paris, France
  • 3Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan
  • 4Research Center for Complex Systems Biology, The University of Tokyo, Tokyo 153-8902, Japan
  • 5Universal Biology Institute, The University of Tokyo, Tokyo 113-0033, Japan
  • 6Santa Marinella Research Institute, 00052 Santa Marinella, Italy

  • *Corresponding author: arthur.genthon@hotmail.fr

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Issue

Vol. 1, Iss. 1 — September - November 2023

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